Implement advanced filtering and sorting capabilities for APIs with query parsing, field validation, and optimization. Use when building search features, complex queries, or flexible data retrieval endpoints.

API Filtering & Sorting Table of Contents [Overview]( overview) [When to Use]( when to use) [Quick Start]( quick start) [Reference Guides]( reference guides) [Best Practices]( best practices) Overview Build flexible filtering and sorting systems that handle complex queries efficiently with proper validation, security, and performance optimization. When to Use Building search and filter interfaces Implementing advanced query capabilities Creating flexible data retrieval endpoints Optimizing query performance Validating user input for queries Supporting complex filtering logic Quick Start Minimal working example: Reference Guides Detailed implementations in the references/ directory: Guide Contents [Query Parameter Filtering](references/query parameter filtering.md) Query Parameter Filtering [Advanced Filter Parser](references/advanced filter parser.md) Advanced Filter Parser [Filter Builder Pattern](references/filter builder pattern.md) Filter Builder Pattern [Python Filtering (SQLAlchemy)](references/python filtering sqlalchemy.md) Python Filtering (SQLAlchemy) [Elasticsearch Filtering](references/elasticsearch filtering.md) Elasticsearch Filtering [Query Validation](references/query validation.md) Query Validation Best Practices ✅ DO Whitelist allowed filter fields Validate all input parameters Index fields used for filtering Support common operators Provide faceted navigation Cache filter options Limit filter complexity Document filter syntax Use database native operators Optimize queries with indexes ❌ DON'T Allow arbitrary field filtering Support unlimited operators Ignore SQL injection risks Create complex filter logic Expose internal field names Filter on unindexed fields Allow deeply nested filters Skip input validation Combine all filters with OR Ignore performance impact

api-filtering-sorting